Skip to Main content Skip to Navigation
Journal articles

Discovery of Probabilistic Mappings between Taxonomies: Principles and Experiments

Rémi Tournaire 1, 2 Jean-Marc Petit 1 Marie-Christine Rousset 2, * Alexandre Termier 2
* Corresponding author
1 BD - Base de Données
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : In this paper, we investigate a principled approach for defining and discovering probabilistic mappings between two taxonomies. First, we compare two ways of modeling probabilistic mappings which are compatible with the logical constraints declared in each taxonomy. Then we describe a generate and test algorithm which minimizes the number of calls to the probability estimator for determining those mappings whose probability exceeds a certain threshold. Finally, we provide an experimental analysis of this approach.
Document type :
Journal articles
Complete list of metadata

Cited literature [58 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-00932491
Contributor : Alexandre Termier Connect in order to contact the contributor
Submitted on : Friday, January 17, 2014 - 11:14:05 AM
Last modification on : Thursday, October 21, 2021 - 3:48:57 AM
Long-term archiving on: : Friday, April 18, 2014 - 11:32:00 AM

File

JoDS_Tournaire_last_submission...
Files produced by the author(s)

Identifiers

`

Citation

Rémi Tournaire, Jean-Marc Petit, Marie-Christine Rousset, Alexandre Termier. Discovery of Probabilistic Mappings between Taxonomies: Principles and Experiments. Journal on Data Semantics, Springer, 2011, 6720, pp.66-101. ⟨10.1007/978-3-642-22630-4_3⟩. ⟨hal-00932491⟩

Share

Metrics

Record views

537

Files downloads

465